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Imaging Studies IV: Magnetic Resonance Imaging01:27

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Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...
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Urinary marker panels for aggressive prostate cancer detection.

Tung-Shing Mamie Lih1, Mingming Dong2, Leslie Mangold3

  • 1Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, MD, 21231, USA. tlih1@jhmi.edu.

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Summary
This summary is machine-generated.

New urinary biomarkers can help differentiate aggressive prostate cancer (PCa) from indolent forms. Multi-marker panels, including urinary glycopeptides and prostate-specific antigen (PSA), show promise for improved PCa detection.

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Area of Science:

  • Biochemistry
  • Oncology
  • Proteomics

Background:

  • Active surveillance is common for indolent prostate cancer (PCa).
  • Accurate classification of PCa into indolent versus aggressive subtypes is crucial for appropriate patient management.
  • Novel biomarkers are needed to distinguish between non-aggressive (Grade Group 1) and aggressive (Grade Group ≥2) PCa.

Purpose of the Study:

  • To investigate the clinical utility of urinary marker panels for distinguishing aggressive PCa from non-aggressive PCa.
  • To evaluate panels composed of urinary glycopeptides and urinary prostate-specific antigen (PSA).

Main Methods:

  • Urinary glycopeptides were analyzed using data-independent acquisition mass spectrometry (DIA-MS).
  • Prostatic acid phosphatase (ACPP), clusterin (CLU), alpha-1-acid glycoprotein 1 (ORM1), and CD antigen 97 (CD97) were quantified.
  • Targeted parallel reaction monitoring (PRM) assays were used for ACPP and CLU glycopeptides.
  • Multi-marker panels were combined using logistic regression and validated in an independent cohort.

Main Results:

  • Several multi-urinary marker panels demonstrated significant clinical utility.
  • A panel including ACPP, CLU, and urinary PSA achieved an area under the curve (AUC) between 0.70 and 0.85.
  • These panels effectively separated Grade Group 1 from Grade Group ≥2 PCa.

Conclusions:

  • Multi-urinary marker panels show clinically meaningful performance in detecting aggressive PCa.
  • These findings support further clinical evaluation of these panels for PCa classification.
  • Urinary glycopeptides combined with PSA represent a promising non-invasive approach for PCa risk stratification.